• Journal of the Chungcheong Mathematical Society
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• v.22 no.2
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• pp.149-153
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• 2009

Let {$X_{n},\;n\;\geq\;1$} be a sequence of independent and identically distributed random variables with absolutely continuous cumulative distribution function (cdf) F(x) and probability density function (pdf) f(x). Suppose $X_{U(m)},\;m = 1,\;2,\;{\cdots}$ be the upper record values of {$X_{n},\;n\;\geq\;1$}. It is shown that the linearity of the conditional expectation of $X_{U(n+2)}$ given $X_{U(n)}$ characterizes the lomax, exponential and pareto distributions.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.3
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• pp.385-396
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• 2016

Characterizations of probability distributions by different regression conditions on generalized order statistics has attracted the attention of many researchers. We present here, characterization of Pareto and Weibull distributions based on the conditional expectation of generalized order statistics extending the characterization results reported by Jin and Lee (2014). We also present a characterization of the power function distribution based on the conditional expectation of lower generalized order statistics.

• Communications of the Korean Mathematical Society
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• v.25 no.3
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• pp.485-489
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• 2010

A family of continuous probability distribution has been characterized through the difference of two conditional expectations, conditioned on a non-adjacent record statistic. Also, a result based on the unconditional expectation and a conditional expectation is used to characterize a family of distributions. Further, some of its deductions are also discussed.

• Water for future
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• v.17 no.4
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• pp.273-279
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• 1984

An attempt is made to present a method of prediction for typhoons apporaching the Korean-peninsula. The method is based upon the Bayesian theorem to improve the observed (prior) probabilities of typhoons approaching the Korean sea area incorporating conditional probability. A total of 248 typhoons is collected and analyzed to establish prior probability and conditional probability according to the defined procedure. The typhoons used are those which encompassed the western Pacific area to which the Korean-peninsula is subjected. The results of examplary computations suggest that the presented method is promising for predicting approaching typhoons.

• Earthquakes and Structures
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• v.11 no.1
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• pp.109-127
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• 2016

This paper examines the contribution of three sources of uncertainties to probabilistic seismic behaviour of wood frame buildings, including ground motions, intensity and seismic mass. This sensitivity analysis is performed using three methods, including the traditional method based on the conditional distributions of ground motions at given intensity measures, a method using the summation of conditional distributions at given ground motion records, and the Monte Carlo simulation. FEMA P-695 ground motions and its scaling methods are used in the analysis. Two archetype buildings are used in the sensitivity analysis, including a two-storey building and a four-storey building. The results of these analyses indicate that using data-fitting techniques to obtain probability distributions may cause some errors. Linear interpolation combined with data-fitting technique may be employed to improve the accuracy of the calculated exceeding probability. The procedures can be used to quantify the risk of wood frame buildings in seismic events and to calibrate seismic design provisions towards design code improvement.

• Korean Journal of Logic
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• v.19 no.2
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• pp.233-251
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• 2016

In their recent paper published in this journal Shin Kim and Jinyong Lee have attacked some previous studies on the counterexample to modus ponens. Among their arguments I would like to discuss the following two; first, those attempts to explain van McGee's example by reference to conditional probability do not accord with van McGee's position, second, van McGee'e example is to be best seen as an argument containing the fallacy of equivocation. I show that the first argument is not correct, the second one is not so persuasive as it seemed first.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.6
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• pp.1007-1019
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• 2015

The determination of the required seawall height is usually based on the combination of wind speed (or wave height) and still water level according to a specified return period, e.g., 50-year return period wind speed and 50-year return period still water level. In reality, the two variables are be partially correlated. This may be lead to over-design (costs) of seawall structures. The above-mentioned return period for the design of a seawall depends on economy, society and natural environment in the region. This means a specified risk level of overtopping or damage of a seawall structure is usually allowed. The aim of this paper is to present a conditional risk probability-based seawall height design method which incorporates the correlation of the two variables. For purposes of demonstration, the wind speeds and water levels collected from Jiangsu of China are analyzed. The results show this method can improve seawall height design accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.847-851
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• 2004

In the original mixture density network(MDN), which was introduced by Bishop and Nabney, the parameters of the conditional probability density function are represented by the output vector of a single multi-layer perceptron. Among the recent modification of the MDNs, there is the so-called modified mixture density network, in which each of the priors, conditional means, and covariances is represented via an independent multi-layer perceptron. In this paper, we consider a further simplification of the modified MDN, in which the conditional means are linear with respect to the input variable together with the development of the MATLAB program for the simplification. In this paper, we first briefly review the original mixture density network, then we also review the modified mixture density network in which independent multi-layer perceptrons play an important role in the learning for the parameters of the conditional probability, and finally present a further modification so that the conditional means are linear in the input. The applicability of the presented method is shown via an illustrative simulation example.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.256-261
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• 2008

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the conditional maximum a posteriori criterion. A crucial component of a practical speech enhancement system is the estimation of the noise power spectrum. One state-of-the-art approach is the minima controlled recursive averaging (MCRA) technique. The noise estimate in the MCRA technique is obtained by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. We improve the MCRA using the speech presence probability which is the a posteriori probability conditioned on both the current observation the speech presence or absence of the previous frame. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and subjective evaluation of speech quality, we show that the proposed algorithm yields better results compared to the conventional MCRA-based scheme.

• The Mathematical Education
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• v.48 no.3
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• pp.353-358
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• 2009

The article discusses the independence concept occurring in the learning of probability. The author does not distinguishes the independence in the events from the independence in the trials. Instead, the author suggests the physico-empirical independence and the logico-mathematical independence to distinguish between the two concepts.